Summary

Dataset 1

Experiments excluded

Mask

Get figure file: figures/preliminary_dset-1_figure-mask.png

Peak coordinates

Get figure file: figures/preliminary_dset-1_figure-static.png
Get figure file: figures/preliminary_dset-1_figure-legend.png

Explorer

Meta-Analysis

Estimator

Parameters use to fit the meta-analytic estimator.

Corrector

Parameters use to fit the corrector.

Corrected meta-analytic map: z_corr-FDR_method-indep

Explorer

The following figure provides an interactive window to explore the meta-analytic map in detail.

Slice viewer

This panel shows the the corrrected meta-analytic map.

Get figure file: figures/corrector_figure-static.png

Diagnostics

Target image: z_corr-FDR_method-indep

Significant clusters

    X Y Z Peak Stat Cluster Size (mm3)
Tail Cluster ID          
Positive 1 52.00 -46.00 8.00 6.71 45520
1a 50.00 -60.00 6.00 6.67
1b 54.00 -52.00 8.00 6.67
1c 46.00 -62.00 4.00 6.48
2 52.00 28.00 0.00 5.90 11424
2a 54.00 30.00 8.00 4.49
2b 42.00 24.00 -4.00 4.49
2c 54.00 26.00 6.00 4.49
3 -44.00 -50.00 -14.00 5.69 26232
3a -42.00 -56.00 -20.00 5.69
3b -56.00 -46.00 8.00 5.69
3c -46.00 -58.00 -20.00 5.69
4 0.00 -58.00 20.00 5.01 6496
4a -6.00 -52.00 32.00 3.66
4b 8.00 -58.00 22.00 3.36
4c -8.00 -58.00 28.00 3.36
5 -20.00 -6.00 -18.00 4.76 2272
5a -24.00 2.00 -14.00 2.77
5b -16.00 -10.00 -12.00 2.47
5c -16.00 2.00 -12.00 2.47
6 -50.00 28.00 6.00 4.49 11176
6a -46.00 28.00 -2.00 4.49
6b -48.00 24.00 12.00 3.94
6c -38.00 24.00 0.00 3.94
7 26.00 0.00 -18.00 4.49 3192
8 22.00 -86.00 -4.00 4.49 2400
8a 30.00 -90.00 0.00 3.07
8b 22.00 -94.00 0.00 2.77
8c 26.00 -84.00 -12.00 2.47
9 -58.00 -4.00 -10.00 3.94 2912
9a -60.00 -20.00 4.00 3.07
9b -54.00 -10.00 -6.00 3.07
9c -56.00 -20.00 -2.00 2.77
10 -24.00 -4.00 58.00 3.94 3456
10a -40.00 0.00 52.00 3.07
10b -26.00 -8.00 52.00 2.77
10c -26.00 4.00 52.00 2.77
11 -6.00 42.00 -8.00 3.66 7480
11a 0.00 52.00 -8.00 3.36
11b 2.00 56.00 8.00 3.36
11c 2.00 54.00 18.00 3.36
12 2.00 8.00 42.00 3.36 4072
12a 0.00 10.00 56.00 3.36
12b -10.00 12.00 60.00 3.07
12c 6.00 10.00 40.00 3.07
13 -38.00 -36.00 56.00 3.36 2072
13a -34.00 -30.00 60.00 2.77
13b -46.00 -38.00 46.00 2.47
13c -36.00 -38.00 48.00 2.47
14 16.00 -86.00 28.00 3.07 2544
14a 6.00 -86.00 18.00 2.77
14b 16.00 -88.00 24.00 2.77
14c 30.00 -84.00 18.00 2.77
15 26.00 0.00 60.00 3.07 1064
15a 22.00 -4.00 54.00 2.47
15b 14.00 -4.00 56.00 1.84
15c 26.00 -4.00 52.00 1.84
16 36.00 -74.00 28.00 3.07 448
16a 32.00 -80.00 24.00 2.15
17 2.00 36.00 44.00 2.77 368
18 22.00 -58.00 60.00 2.77 1056
18a 26.00 -66.00 56.00 1.84
19 -48.00 10.00 -30.00 2.77 664
19a -48.00 4.00 -36.00 2.15
20 -36.00 -82.00 -6.00 2.47 216
21 42.00 4.00 44.00 2.47 112
22 -22.00 -54.00 -16.00 2.15 120
23 -28.00 8.00 -18.00 2.15 120
24 -48.00 4.00 26.00 2.15 112
25 -14.00 -90.00 -4.00 2.15 88
25a -12.00 -90.00 4.00 1.84
26 -8.00 10.00 2.00 1.84 96

Label map: positive tail

Get figure file: figures/diagnostics_tail-positive_figure.png

FocusCounter

The FocusCounter analysis characterizes the relative contribution of each experiment in a meta-analysis to the resulting clusters by counting the number of peaks from each experiment that fall within each significant cluster.

The heatmap presents the relative contributions of each experiment to each cluster in the thresholded map. There is one row for each experiment, and one column for each cluster, with column names being PostiveTail/NegativeTail indicating the sign (+/-) of the cluster's statistical values. The rows and columns were re-ordered to form clusters in the heatmap.

Heatmap: positive tail

Methods

We kindly ask to report results preprocessed with this tool using the following boilerplate.

A multilevel kernel density (MKDA) meta-analysis \citep{wager2007meta} was performed was performed
with NiMARE 0.6.1 (RRID:SCR_017398; \citealt{Salo2023}), using a(n) MKDA kernel. An MKDA kernel
\citep{wager2007meta} was used to generate study-wise modeled activation maps from coordinates. In
this kernel method, each coordinate is convolved with a sphere with a radius of 10.0 and a value of
1. For voxels with overlapping spheres, the maximum value was retained. Summary statistics (OF
values) were converted to p-values using an approximate null distribution. The input dataset
included 2608 foci from 325 experiments. False discovery rate correction was performed with the
Benjamini-Hochberg procedure \citep{benjamini1995controlling}.

Bibliography

@article{Salo2023,
  doi = {10.52294/001c.87681},
  url = {https://doi.org/10.52294/001c.87681},
  year = {2023},
  volume = {3},
  pages = {1 - 32},
  author = {Taylor Salo and Tal Yarkoni and Thomas E. Nichols and Jean-Baptiste Poline and Murat Bilgel and Katherine L. Bottenhorn and Dorota Jarecka and James D. Kent and Adam Kimbler and Dylan M. Nielson and Kendra M. Oudyk and Julio A. Peraza and Alexandre Pérez and Puck C. Reeders and Julio A. Yanes and Angela R. Laird},
  title = {NiMARE: Neuroimaging Meta-Analysis Research Environment},
  journal = {Aperture Neuro}
}
@article{benjamini1995controlling,
  title={Controlling the false discovery rate: a practical and powerful approach to multiple testing},
  author={Benjamini, Yoav and Hochberg, Yosef},
  journal={Journal of the Royal statistical society: series B (Methodological)},
  volume={57},
  number={1},
  pages={289--300},
  year={1995},
  publisher={Wiley Online Library},
  url={https://doi.org/10.1111/j.2517-6161.1995.tb02031.x},
  doi={10.1111/j.2517-6161.1995.tb02031.x}
}
@article{wager2007meta,
  title={Meta-analysis of functional neuroimaging data: current and future directions},
  author={Wager, Tor D and Lindquist, Martin and Kaplan, Lauren},
  journal={Social cognitive and affective neuroscience},
  volume={2},
  number={2},
  pages={150--158},
  year={2007},
  publisher={Oxford University Press},
  url={https://doi.org/10.1093/scan/nsm015},
  doi={10.1093/scan/nsm015}
}